• Journal of Distribution Science
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• v.13 no.1
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• pp.93-103
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• 2015

Purpose - This study plans to adopt a more sophisticated approach toward service recognition by customers in general supermarkets in order to revise the service quality measurement methods that suit the context of Korean distribution channels. In particular, in general supermarkets, where much of the shopping process is in the form of self-service, there is high reliance on the service recognized by the consumers; therefore, it is highly likely that consumers would make their purchasing decisions based on their recognition of service quality or guarantees. It also utilized service quality elements of a basic level in the KD-SQS development model in order to indicate that the quality recognized by consumers impacts their loyalty to the stores with financial value and abstract value. Research design, data, and methodology - The study suggested a theoretical model comprising 13 hypotheses on relations between theoretic variables, and conducted surveys with consumers using discount stores in Seoul and Gyunggi Metropolitan area in order to verify the hypotheses, while using SPSS 20.0, AMOS 21.0 as the verification program. The survey sheets used amounted to 332, and a structural equation model was used to analyze the reliability and validity of constituent elements and to verify the suggested hypothesis. Therefore, this study analyzes the interrelations between service quality and guarantee factors in the distribution channel and their relations with the loyalty to stores as a dependent variable. Results - First, the results of the hypotheses tests helped identify the relations between service quality, service guarantees, service value, and customer loyalty, providing an opportunity to define the relations between constituent elements. In particular, service convenience in service quality has no impact on financial values. Further, stores' service policy had no impact on abstract values. Service recognition by service convenience has an impact on abstract values such as good image, comfort, and usability, while mileage systems promote financial values for consumers. In order to improve consumer values in service quality and values, general supermarkets should improve their service convenience, membership, and mileage programs using various strategies. Conclusion - In order to improve consumer values in service quality and values, general supermarkets should improve their service convenience, membership, and mileage programs using various strategies. Further, as service guarantee systems have a significant and direct impact on customer loyalty, rather than customer value recognition, service guarantees should be used to encourage customers to re-visit the stores. Finally, this study applied the findings of preceding studies in terms of service quality measurement; it had limitations in referencing preceding studies in a comprehensive manner. It also had limits in expanding upon various preceding studies because it was difficult to apply new measurement tools due to the lack of service quality measurement tools for general supermarkets. Therefore, it is necessary to conduct more studies on service quality to measure service quality and develop measurement tools by incorporating various industry characteristics.

• Journal of radiological science and technology
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• v.44 no.5
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• pp.513-523
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• 2021

The purpose of this study was to discuss the required items and feasibility of medical records of radiological examinations performed by radiological technologists at medical institutions. An online survey was conducted to a total of 10,000 radiation-related workers, of which 1,026 (10.3%) responded. As a research method, self-made questionnaires were used. The online survey was conducted from September 10 to September 20, 2021 for the survey period. For response data, a Chi-square test was performed according to demographic characteristics using SPSS 27.0 version (IBM Inc., Chicago, Ill, USA), and it was judged to be significant when the P value was less than 0.05. The reliability of the questionnaire response was found to be Chronbach α=0.933. More than 90% of the medical records related to radiological examinations are necessary, and they answered that a curriculum, remuneration curriculum, and legal system for medical records should be prepared. More than 90% of the respondents agreed with the proposal of the Radiological Technologist Independent Act for legal preparation, and most of the information required for medical records is currently recorded in DICOM images. According to the demographic characteristics, the medical record requirement for radiological examination, curriculum, continuing education, and legislation were found to be higher with higher education and higher with longer working experience. In addition, most of the radiology departments showed a high demand for medical records, so most of them responded positively to the medical records requirements for radiological examinations. This study analyzed the medical record requirements for radiological examinations, and as shown in the results, medical record requirements for radiological examinations was found that most radiological technologists felt need for the new law and supported it. In addition, if the information recorded in the DICOM image is used, it is considered that medical records could be easily prepared without additional work by the radiological technologists.

• Journal of the Korea Convergence Society
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• v.12 no.12
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• pp.453-465
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• 2021

This study was attempted to identify factors affecting depression by stress causes. Data from the 2018 Korea National Health and Nutrition Examination Survey were used, total subjects was 2,939. Data were analyzed by complex sample frequency, percentage, x2-test and regression by SPSS 25.0. As a result, in the economic problem group, gender, occupation, health-related quality of life, weight change, smoking, subjective health status and subjective body image were significant influencing factors for depression, and explanatory power was 28.7% (F = 8.23, p < .001). In the parent, child, and spouse problem group, age, health-related quality of life, weight change, and subjective health status were significant, explanatory power was 33.1% (F = 6.92, p <.001). In the self and family health problem group, gender, health-related quality of life, weight change, smoking, and subjective health status were significant, explanatory power was 29.6% (F = 5.74, p < .001). Through the results, the influencing factors that appear differently according to each stress cause can be used as basic data to establish an individualized intervention strategy.

• Journal of Internet Computing and Services
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• v.19 no.6
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• pp.41-51
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• 2018

Recently, in the field of video surveillance, deep learning based learning method is applied to intelligent video surveillance system, and various events such as crime, fire, and abnormal phenomenon can be robustly detected. However, since occlusion occurs due to the loss of 3d information generated by projecting the 3d real-world in 2d image, it is need to consider the occlusion problem in order to accurately detect the object and to estimate the pose. Therefore, in this paper, we detect moving objects by solving the occlusion problem of object detection process by adding depth information to existing RGB information. Then, using the convolution neural network in the detected region, the positions of the 14 keypoints of the human joint region can be predicted. Finally, in order to solve the self-occlusion problem occurring in the pose estimation process, the method for 3d human pose estimation is described by extending the range of estimation to the 3d space using the predicted result of 2d keypoint and the deep neural network. In the future, the result of 2d and 3d pose estimation of this research can be used as easy data for future human behavior recognition and contribute to the development of industrial technology.

• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.3
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• pp.419-432
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• 2019

Most of deep learning model training was proceeded by supervised learning, which is to train labeling data composed by inputs and corresponding outputs. Labeling data was directly generated manually, so labeling accuracy of data is relatively high. However, it requires heavy efforts in securing data because of cost and time. Additionally, the main goal of supervised learning is to improve detection performance for 'True Positive' data but not to reduce occurrence of 'False Positive' data. In this paper, the occurrence of unpredictable 'False Positive' appears by trained modes with labeling data and 'True Positive' data in monitoring of deep learning-based CCTV accident detection system, which is under operation at a tunnel monitoring center. Those types of 'False Positive' to 'fire' or 'person' objects were frequently taking place for lights of working vehicle, reflecting sunlight at tunnel entrance, long black feature which occurs to the part of lane or car, etc. To solve this problem, a deep learning model was developed by simultaneously training the 'False Positive' data generated in the field and the labeling data. As a result, in comparison with the model that was trained only by the existing labeling data, the re-inference performance with respect to the labeling data was improved. In addition, re-inference of the 'False Positive' data shows that the number of 'False Positive' for the persons were more reduced in case of training model including many 'False Positive' data. By training of the 'False Positive' data, the capability of field application of the deep learning model was improved automatically.

• Journal of Internet of Things and Convergence
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• v.8 no.6
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• pp.115-122
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• 2022

Recently, the importance of CPR training for the layperson has been emphasized to improve the survival rate of out-of-hospital cardiac arrest patients. An accurate and realistic training strategy is required for the CPR training effect for laypersons. In this study, we develop an extended reality (XR) based CPR training system and evaluate its usability. The XR based CPR training system consisted of three applications. First, a 3D heart anatomy image registered to the manikin is transmitted to the smart glasses to guide the chest compression point. The second application provides visual and auditory information about the CPR process through smart glasses. At the same time, the smartwatch sends a vibration notification to guide the compression rate. The 'Add-on-kit' is a device that detects the depth and speed of chest compression via sensors installed on the manikin and sends immediate feedback to the smartphone. One hundred laypersons who participated in this study agreed that the XR based CPR training system has realism and effectiveness. XR based registration technology will contribute to improving the efficiency of CPR training by enhancing realism, immersion, and self-directed learning.

• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.944-953
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• 2020

Object detection plays a crucial role in a self-driving system. With the advances of image recognition based on deep convolutional neural networks, researches on object detection have been actively explored. In this paper, we proposed a lightweight model of the mask R-CNN, which has been most widely used for object detection, to efficiently predict location and shape of various objects on the road environment. Furthermore, feature maps are adaptively re-calibrated to improve the detection performance by applying an attention module to the neural network layer that plays different roles within the mask R-CNN. Various experimental results for real driving scenes demonstrate that the proposed method is able to maintain the high detection performance with significantly reduced network parameters.

• Economic and Environmental Geology
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• v.55 no.3
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• pp.309-316
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• 2022

In order to minimize the human and time consumption required for rock classification, research on rock classification using artificial intelligence (AI) has recently developed. In this study, basic volcanic rocks were subdivided by using polarizing microscope thin section images. A convolutional neural network (CNN) model based on Tensorflow and Keras libraries was self-producted for rock classification. A total of 720 images of olivine basalt, basaltic andesite, olivine tholeiite, trachytic olivine basalt reference specimens were mounted with open nicol, cross nicol, and adding gypsum plates, and trained at the training : test = 7 : 3 ratio. As a result of machine learning, the classification accuracy was over 80-90%. When we confirmed the classification accuracy of each AI model, it is expected that the rock classification method of this model will not be much different from the rock classification process of a geologist. Furthermore, if not only this model but also models that subdivide more diverse rock types are produced and integrated, the AI model that satisfies both the speed of data classification and the accessibility of non-experts can be developed, thereby providing a new framework for basic petrology research.

• The Journal of the Korea Contents Association
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• v.22 no.7
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• pp.599-606
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• 2022

This study investigates trends and changes in gender expression in film and animation. It compares how gender, race, and class discrimination that was socially and culturally expressed differently in past and modern media contents. Indiscriminate content appreciation by the "digital native" generation is likely to unconsciously create false stereotypes. In this study, 「Aladdin」(1992) and 「Aladdin」(2019) were analyzed. This study looks at in the characters have changed since the original, which was a 2D animation in 1992, was re-released as a live-action film in 2019. For character analysis, we compare and analyze major characters and find out the differences based on the nine personality types of Enneagram, which define human personality types. As a result, Princess Jasmine's character change was remarkable. In the past, Disney animations had the majority of patriarchal and male-dependent princess characters, but now Disney is aiming for self-directed and independent female characters. Also, scenes that could instill stereotypes of gender, race, and class were changed. Disney's change can be seen as expressing the gender image that the public wants. Analysis of the change in character's personality in these works can be a useful methodology for creating attractive characters for the public.

• Journal of the Korean Society of Floral Art and Design
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• no.44
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• pp.53-73
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• 2021

This study is on the creation of art works through the methodological process of deducting the experiences and inspired feeling which the researcher experienced in the subconscious level as well as the conscious level in the field of floral art creation. The scene setting technique was applied to seize inner experiences and feeling in subconscious level. More concretely, visual note technique and image research technique were applied to record and preserve scenes as the seized inner mental images. To delineate the contents, the researcher created art works based on the experiences during the preparation period at the small town of Tours in France as well as the competitive and tough every day life during the attendance at the fashion school of ESOMD International Paris. The researcher was able to create 5 art works of Deja Vu, 'ㅅ(Seoul-Paris)', '崩(A Mountain on Two Moons)', '燈 (Load out and Stay)', 'ㅇ'deducting the deep experiences and inspired feeling through the methodological process in the subconscious level as well as the conscious level. The researcher was able to explore inner experiences finding self in disquietude and process of personal realization through the creation. The meaning of this research could be found as a case of qualitative research which presents approaches utilizing method of deducting experiences in subconscious level and applying to the creation of art works.